Rod Defects Research Articles

Deep Learning-Based Intelligent Detection Device for Insulation Pull Rod Defects

Deep Learning-Based Intelligent Detection Device for Insulation Pull Rod Defects

Nascent flagellar basal bodies are immobilized by rod assembly in Bacillus subtilis.

Bacteria insert flagella in a species-specific pattern on the cell body, but how patterns are achieved is poorly understood. In bacteria with a single polar flagellum, a marker protein localizes to the cell pole and nucleates the assembly of the flagellum at that site. Bacillus subtilis assembles ∼15 flagella over the length of the cell body in a grid-like pattern and lacks all proteins associated with targeted assembly in polarly flagellated bacteria. Here we show that B. subtilis basal bodies are mobile soon after assembly and become immobilized when the flagellar rod transits the peptidoglycan wall. Moreover, defects in the flagellar rod lead to an asymmetric distribution of flagella with respect to the midcell. We conclude that the patterning of flagella is different in B. subtilis , and we infer that the B. subtilis rod probes the peptidoglycan for holes that can accommodate the machine.

Analysis of heating defects in extension rods of extra-high voltage direct current overhead transmission lines

This paper studies the overheating defect of an extension rod in a ± 800 kV extra-high voltage direct current overhead transmission line, and proposes various factors that affect the overheating of the extension rod. Establish an equivalent model of an extra high voltage DC transmission line based on equipotential point and line parameter analysis, and calculate the model parameters. The proposed model can also be applied to ultra-high voltage DC overhead transmission lines such as ± 500 kV, and has strong universality. Simulation experiments show that if the equivalent resistance value of the split wire side is reduced by 0.01Ω, the power loss on the extension tie rod can be increased to 380.951 W; if the equivalent resistance value of the jumper side is increased by 0.01Ω, the power loss on the extension tie rod can be increased to 273.41 W. Combined with theoretical analysis and simulation verification, it is concluded that the main factor affecting the overheating of the extension rod is the change in the resistance value on the jumper side caused by the increase in contact resistance. A systematic troubleshooting plan for related defect problems is proposed, which has important reference and guidance significance for such line fault problems.

Simulation and Characterization of Micro-Discharge Phenomena Induced by Glitch Micro-Defects on an Insulated Pull Rod Surface

The reliability of GIS (gas-insulated switchgear) circuit breakers significantly depends on the condition of the insulated pull rods, with micro-defects on their surface posing a potential risk for micro-discharges and breakdown incidents. Experimentally investigating these micro-discharges is challenging due to their minute nature. This study introduces a framework to examine the linkage between micro-defects and micro-discharges, coupled with numerical simulations of the micro-discharge process in insulated pull rods afflicted by surface infiltration flaws under operational conditions. Initially, samples containing micro-defects were sectioned via water jet cutting for microstructural analysis through white light interferometry. Subsequently, a two-dimensional axisymmetric model simulating positive corona discharge from a needle to a plate electrode was employed to derive the relationship between charged particle density and the electric field in SF6 and air. Building on these observations, a micro-discharge model specific to micro-defects was developed. Comparative analysis of micro-discharge behaviors in SF6 and air for identical defect types was conducted. This research framework elucidates the discharge dynamics of charged particles in SF6 and air during micro-discharge events, shedding light on the mechanisms underpinning micro-discharges triggered by insulation rod defects.

Intelligent identification method of insulation pull rod defects based on intactness‐aware Mosaic data augmentation and fusion of YOLOv5s

AbstractThe authors introduce the intactness‐aware Mosaic data augmentation strategy, designed to tackle challenges such as low accuracy in detecting defects in insulation pull rods, limited timeliness in intelligent analysis, and the absence of a comprehensive database for information on insulation pull rod defects. The proposed strategy incorporates the YOLOv5s algorithm for detecting defects in insulation pull rods. Initially, the YOLOv5s network was constructed, and a dataset containing photos of insulation pull rods with white spots, fractures, impurities, and bubble flaws was compiled to capture images of defects. The research presented a data enhancement approach to improve the images and establish a dataset for insulation pull rod defects. The YOLOv5s algorithm was applied for both training and testing purposes. A comparative analysis was conducted to assess the detection performance of YOLOv5s against a conventional target detector for identifying defects in insulation pull rods. Furthermore, the utility of Mosaic's data augmentation technique, which incorporates intactness awareness, was evaluated to enhance the accuracy of identifying insulation pull rod defects. The research findings indicate that the YOLOv5s algorithm is employed for intelligent detection and precise localisation of flaws. The intactness‐aware Mosaic data augmentation strategy significantly improves the accuracy of detecting faults in insulation pull rods. The YOLOv5s model used achieves a performance index mAP@0.5:0.95 of 0.563 on the test set, distinct from the training set data. With a threshold of 0.5, the mAP@0.5 score is 0.904, indicating a substantial improvement in both detection efficiency and accuracy compared to conventional target detection methods. Innovative approaches for identifying defects in insulation pull rods are introduced.

Diagnosis Method of Decay-like Composite Insulators in a High-Humidity Environment Based on Characteristic Coefficient of Temperature Rise Gradient.

At present, the temperature rise in insulators is observed using infrared thermometry as a common method of diagnosing decay-like insulators. However, the original characteristic data obtained by infrared thermometry cannot effectively distinguish some of the decay-like insulators from those with ageing sheaths. Therefore, it is imperative to find a new diagnostic characteristic quantity. Based on statistical data, this article first explains that existing diagnostic methods have limited diagnostic effectiveness and a high false detection rate for insulators in a slightly heated state. A full-scale temperature rise test is carried out on a batch of composite insulators returned from the field under high-humidity conditions. Two different defective insulators with similar temperature rise profiles are identified, and an electro-thermal coupling simulation model is developed based on the dielectric characteristic parameters of the above insulators for both core rod defects and sheath ageing. A new infrared diagnostic feature, the temperature rise gradient coefficient, is then obtained to identify the source of abnormal heat in insulators using statistical analysis of an infrared image gallery of abnormally hot composite insulators obtained from field inspections and laboratory tests.

Changes to Material Phase and Morphology Due to High-Level Molybdenum Doping of ZnO Nanorods: Influence on Luminescence and Defects.

The influence of Mo on the electronic states and crystalline structure, as well as morphology, phase composition, luminescence, and defects in ZnO rods grown as free-standing nanoparticles, was studied using a variety of experimental techniques. Mo has almost no influence on the luminescence of the grown ZnO particles, whereas shallow donors are strongly affected in ZnO rods. Annealing in air causes exciton and defect-related bands to drop upon Mo doping level. The increase of the Mo doping level from 20 to 30% leads to the creation of dominating molybdates. This leads to a concomitant drop in the number of formed ZnO nanorods.

Cellular and Molecular Mechanisms of Pathogenesis Underlying Inherited Retinal Dystrophies.

Inherited retinal dystrophies (IRDs) are congenital retinal degenerative diseases that have various inheritance patterns, including dominant, recessive, X-linked, and mitochondrial. These diseases are most often the result of defects in rod and/or cone photoreceptor and retinal pigment epithelium function, development, or both. The genes associated with these diseases, when mutated, produce altered protein products that have downstream effects in pathways critical to vision, including phototransduction, the visual cycle, photoreceptor development, cellular respiration, and retinal homeostasis. The aim of this manuscript is to provide a comprehensive review of the underlying molecular mechanisms of pathogenesis of IRDs by delving into many of the genes associated with IRD development, their protein products, and the pathways interrupted by genetic mutation.

A Study on the Application of Machine and Deep Learning Using the Impact Response Test to Detect Defects on the Piston Rod and Steering Rack of Automobiles.

The main parts of automobiles are the piston rod of the shock absorber and the steering rack of the steering gear, and their quality control is critical in the product process. In the process line, these products are normally inspected through visual inspection, sampling, and simple tensile tests; however, if there is a problem or abnormality, it is difficult to identify the type and location of the defect. Usually, these defects are likely to cause surface cracks during processing, which in turn accelerate the deterioration of the shock absorber and steering, causing serious problems in automobiles. As a result, the purpose of this study was to present, among non-destructive methods, a shock response test method and an analysis method that can efficiently and accurately determine the defects of the piston rod and steering rack. A test method and excitation frequency range that can measure major changes according to the location and degree of defects were proposed. A defect discrimination model was constructed using machine and deep learning through feature derivation in the time and frequency domains for the collected data. The analysis revealed that it was possible to effectively distinguish the characteristics according to the location as well as the presence or absence of defects in the frequency domain rather than the time domain. The results indicate that it will be possible to quickly and accurately check the presence or absence of defects in the shock absorber and steering in the automobile manufacturing process line in the future. It is expected that this will play an important role as a key factor in building a smart factory.

Influence of point defect accumulation on in-pile thermal conductivity degradation: Fuel rod defect distribution and deviation between in-pile and post irradiation thermal conductivity

As nuclear fuel burn-up increases, its thermal conductivity degrades due to the accumulation of defects that lead to increased phonon scattering rates. This results in a rise in the centerline temperature of the fuel rod, whereby heat generation must be decreased to avoid undesired behavior such as fuel melting and extensive fission gas release. Fuel performance codes are utilized to optimize the fuel's operational conditions; while they are based on established physical principles, their empirical nature limits their predictive capabilities. Recently, an effort has been made to develop predictive fuel performance codes for commonly used nuclear fuels, as well as accelerated qualification of advanced nuclear fuels. In this report, we elaborate on the importance of careful analysis of point defects’ impact on thermal conductivity in fuel performance analysis. A model is presented where point defect concentration is estimated based on Rate Theory modeling and used as input to the Klemens-Callaway model to calculate their contribution to the degradation of thermal conductivity in UO2 under prototypical irradiation conditions. This analysis suggests that point defect concentration is significant at the rim of the fuel pellet and neglecting this leads to underestimation of the centerline temperature, which may have consequences on fission gas behavior.

Defect identification method of carbon fiber sucker rod based on GoogLeNet-based deep learning model and transfer learning

Carbon fiber sucker rods are widely used in oil production site due to their light weight, high strength and corrosion resistance, but there is still a lack of effective internal defect detection methods during production and installation. Aiming at the characteristics of irregular interface in the sucker rod, a novel defect identification method of carbon fiber sucker rod based on multi-sensor information fusion and GoogLeNet-based deep learning model was proposed to identify online the internal defects of carbon fiber sucker rod. First, the full coverage scan of the sucker rod in the cross-section was performed by a water-immersed ultrasonic array containing 32 probes, and the corresponding ultrasonic reflection signals was obtained. Then, a multi-sensor information fusion method was proposed to integrate amplitude and flight time of received ultrasonic reflection signals with the spatial angle information of each probe into defect images. Time signal waveforms of ultrasonic signals with different defects were mapped into different defect images, so that we can rely on deep learning models in the field of image identification to identify those defects. Finally, A GoogLeNet-based deep learning model were trained to identify the image-based defect of the carbon fiber rod. The transfer learning method, which transferred weights of the pre-trained GoogLeNet model by ImageNet large database to the GoogLeNet-based defect identification model, was adopted to enhance the convergence speed and generalization ability of the model for insufficient training samples. The testing results show that the overall defect identification accuracy of the trained GoogLeNet-based deep learning model was 99.72%, which can identify effectively four typical defects and no defects of carbon fiber sucker rods.

Controllable biomimetic mineralization and characterization of hydrated magnesium carbonates using sodium carboxymethyl cellulose

Recently, fixing CO2 within minerals is an environmentally friendly way of CO2 sequestration and utilization strategy. Inspired by cyanobacteria mediated carbonation of hydrated magnesium carbonates (HMCs), the indirect CO2 biomimetic mineralization process involving NH4HCO3-MgCl2 using NaCMC was investigated to obtain HMCs with complex superstructures. The crystal phase, morphology, structure, thermal stability and surface of HMCs were characterized by XRD, SEM, TG and XPS methods. The HMCs products are composed of urchin-like particles assembled by nesquehonite rods at a low NaCMC concentration. At a higher NaCMC concentration, Dypingite flowers assembled by nanosheets generate in situ at the dissolution defects of nesquehonite rod by increasing the NaCMC concentration. The irregular dypingite agglomerates assembled by adjacent flower-like structures and the well-developed dypingite spheres composed of intensive plate-like crystallites are synthesized at temperature above 65 °C. By adjusting the molar ratio of Mg2+/HCO3−, dypingite flakes grow on the top of nesquehonite rods. The superstructure of HMCs was destroyed when increasing the solution pH from 8 to 10. The decomposition of HMCs is characterized by dehydration (or dehydroxylation) and decarbonation stages. XPS confirms that the surface properties for nesquehonite and dypingite are quite different. This study provides insights into the preparation of HMCs with complex hierarchical structures based on biomimetic carbonation.

Disease-associated microglial activation prevents photoreceptor degeneration by suppressing the accumulation of cell debris and neutrophils in degenerating rat retinas.

Retinitis pigmentosa initially presents as night blindness owing to defects in rods, and the secondary degeneration of cones ultimately leads to blindness. Previous studies have identified active roles of microglia in the pathogenesis of photoreceptor degeneration in RP. However, the contribution of microglia to photoreceptor degeneration remains controversial, partly due to limited knowledge of microglial phenotypes during RP.Rationale: In this study, we investigated the pathways of microglial activation and its contribution to photoreceptor degeneration in RP.Methods: A classic RP model, Royal College of Surgeons rat, was used to explore the process of microglial activation during the development of RP. An inhibitor of colony-stimulating factor 1 receptor (PLX3397) was fed to RCS rats for sustained ablation of microglia. Immunohistochemistry, flow cytometry, RT-qPCR, electroretinography and RNA-Seq were used to investigate the mechanisms by which activated microglia influenced photoreceptor degeneration.Results: Microglia were gradually activated to disease-associated microglia in the photoreceptor layers of RCS rats. Sustained treatment with PLX3397 ablated most of the disease-associated microglia and aggravated photoreceptor degeneration, including the secondary degeneration of cones, by downregulating the expression of genes associated with photoreceptor function and components and exacerbating the impairment of photoreceptor cell function. Disease-associated microglial activation promoted microglia to engulf apoptotic photoreceptor cell debris and suppressed the increase of infiltrated neutrophils by increasing engulfment and inhibiting CXCL1 secretion by Müller cells, which provided a healthier microenvironment for photoreceptor survival.Conclusions: Our data highlight a key role of disease-associated microglia activation in the suppression of rod and cone degeneration, which reduces secondary damage caused by the accumulation of dead cells and infiltrated neutrophils in the degenerating retina.

Calculation of Backscattered Ultrasonic Waves Field from a Copper-clad Steel Rod Immersing in Water and Effect of Clad Corrosion and Interfacial Disbond between Clad and Rod Defects on this Field using the Finite Element Method

Inspection and specificity of the intactness of multi-layer and small-size parts like copper-clad steel rod is a hard task and requires high accuracy. The intactness of these parts is crucial due to their importance. One of the inspection methods for these parts is using ultrasonic waves. The scattering phenomenon occurs when these waves impact curved shape bodies under a special condition. The ultrasonic scattering waves contain a lot of information from the physical conditions and mechanical properties of the part. However, using these waves requires high accuracy and attention due to their complexity. One result of the ultrasonic scattering waves is the far-field backscattered frequency spectrum, form function. For the first time in this research, the form function of a copper-clad steel rod that is immersed in water is calculated using the finite element method (FEM) available in the commercial ABAQUS software. For validating the proposed model, the simulation results are compared with analytical and experimental results in the normalized frequency range of 4 £ Ka £ 10. A good agreement is observed between the three methods at the resonance frequencies, and in the overall form of obtained form function. Furthermore, the effects of the two most common defects in these rods, i.e., the corrosion and interfacial disbond between the clad and steel rod, is studied. Results show that this method can properly specify the corrosion percentage and location, and also the length and location of the interfacial disbond defect.

Determination of the variable density of the rod from natural frequencies of longitudinal vibrations

Rods of various configurations are elements of many structures and machines. Therefore, the acoustic and vibration diagnostics of such parts has been widely developed. The paper considers the problem of determining the variable density of the rod from the natural frequencies of longitudinal vibrations. It is assumed that the density changes along the axis and is described by a polynomial function. This approach allows one to determine the law of density variation from a finite set of eigenvalues. The results of the study can find applications for finding hidden defects in steel and composite rods, which arise during the production process or due to corrosion.

Non-Destructive Acoustical Rock Bolt Testing System with Intelligent Filtering in Salt Mine ‘Wieliczka’

This article presents the application of a self-excited acoustic SAS system for non-destructive testing (NDT) for roof-bolt housings in laboratory and real mine conditions. The proposed system with a filtering mechanism was applied to the J64-27 composite anchors. The conducted tests allowed successful confirmation of the usefulness of the system in the detection of rod defects, damage of the mechanism coupling the anchor to the rock mass and testing of the stress state of the anchor itself. The proposed filtering system allowed eliminating the effect of jump change of frequency in the limit cycle of self-excited system. The proposed method is a novel solution for safety diagnostics of bolt housings in mining applications.

The inverse non-stationary problem of identification of defects in an elastic rod

Non-stationary inverse problems of deformed solid mechanics are among the most underexplored due to, inter alia, increasing dimension of non-stationary problems per unit as compared with stationary and static problems, as well as necessity to consider the initial conditions. In the context of the continuing progress of the aviation and aerospace industries, the question arises about technical condition monitoring of aircraft for the purposes of their safe operation. A large proportion of an aircraft structure consists of beam and rod elements exposed to various man-made and natural effects which cause defects inaccessible for visual inspection and required to be identified well in advance. It is well known that defects (such as cracks, cavities, rigid and elastic inclusions) are concentrators of stresses and largely cause processes, which lead to the destruction of elastic bodies. Therefore, the problem of identification of such defects and their parameters, i.e. the problem of identification, represents a great practical interest. Mathematically, the problem of identification represents a non-linear inverse problem. The development of methods of solving such problems is currently a live fundamental research issue.

Investigation of C92900 bronze properties obtained by permanent mold casting, continuous upcasting and hot extrusion

In mechanical engineering, the antifriction tin bronzes, and C92900 bronze for instance are used for parts subjected to wear. The permanent mold casting into steel molds are commonly used to produce parts from C92900 bronze. This work investigates the possibility of C92900 bronze rods production by hot extrusion and upcasting methods. It has been discovered the hot extrusion temperature and ram speed, as well as the casting speed for upcasting that promote no defects in rods. It has been shown that hot extrusion leads to severe grain refinement up to 1.7 gm, and when casting upwards, on the contrary, an increase in the grain size occurs in comparison with the permanent mold casting. After hot extrusion and upcasting, the crystals of the Y-Cu3Sn intermetallic phase are refined in the bronze microstructure. At the same time, large agglomerations of (Pb) particles can be observed in the extruded bronze microstructure, which leads to a decrease in the coefficient of friction. The maximum hardness and tensile strength were obtained for rods produced by hot extrusion at 600 °C, and the highest elongation in rods obtained by the upcasting method. Tribological studies were carried out according to the «shaft — partial insert» scheme in a kerosene medium with a steel counter body showed that hot extrusion leads to a tenfold increase in wear resistance and a threefold decrease in the friction coefficient in comparison with rods obtained by permanent mold casting. At the same time, for the rods obtained by the upcast method, on the contrary, a decrease in wear resistance is observed. In connection with the mentioned results, it is possible to recommend the hot extrusion method for producing C92900 bronze rods in addition with casting technique.

Acoustic Emission Analysis for Damage Mechanism in Fiber Reinforced Polymer Composite under Torsional Behaviour

In this study the torsional behaviour of fiber reinforced polymer (FRP) composite rods of different matrix materials like PEEK, Aqua bond, Epoxy are studied and different types of failures are observed. The FRP composite rods are fabricated by using Vacuum Assisted Resin Transfer Moulding (VARTM) method as per the standards. FRP composite rods are tested in the digital torsion testing machine (MTS100NM). The Acoustic Emission (AE) sensors are used to analyse the nature of the cracks. The defects in FRP composite rods are identified, like surface micro cracks, matrix failure and reinforcement failure. After getting AE signals based on different AE Parameters like Time, Frequency, AE hits and AE energy from the obtained results the failure initiation and crack propagation are identified, Hence the AE method is best suitable technique for identify the micro failures.

Research on the Application of Phased Array Detection Technology in Composite Insulator Interface Debonding Detection

The main reasons for the failure of composite insulator are the fracture of core rod and the breakdown of interface. However, due to the particularity of composite insulator, the traditional insulator detection method is not fully applicable to it. In this paper, phased array detection technology is used to detect the interface debonding defects of composite insulator sheath and core rod, and clear interface debonding signals are obtained. The research results can provide research basis for the application of phased array detection technology in the field of composite insulator defect detection.