Circuit Inspection Research Articles

Stower-13: A Multi-View Inspection Image Dataset for the Automatic Classification and Naming of Tension Towers

In high-voltage transmission lines, the tension tower needs to withstand the tension load of the overhead power line for a long time, which is prone to damage, and it is an important part of the inspection in the circuit inspection. In the modern circuit inspection process, operation and maintenance personnel mostly use unmanned aerial vehicles (UAVs) to photograph various parts of the tension tower, obtain inspection images, and manually classify and name the massive inspection images, which is low in accuracy and efficiency. Based on the above problems, this paper collects a large number of real-life UAV inspection images of various parts of a tension tower, and proposes the Stower-13 inspection image dataset, which is used to train the classification model to achieve automatic classification and naming of inspection images. Based on this dataset, this paper also proposes an improved MobileViT model, in which the Scale-Correlated Pyramid Convolution Block Attention Block (SCPCbam) module is introduced, which adds the Convolution Block Attention Module (CBAM) to the four branches of the original Scale-Correlated Pyramid Convolution (SCPC) module, so as to strengthen the ability of image multi-scale information extraction and improve the classification accuracy. This paper discusses a number of experiments on the model, and the experimental results show that the dataset proposed in this paper helps the model to understand the feature information. At the same time, the improved MobileViT model has a strong ability to extract image spatial feature information, the classification accuracy is higher than that of other models of the same type, so it is able to cope with a wide range of problems that arise in the course of practice, and it meets the practical needs of automatically naming transmission line inspection images.

A Novel Method for Recognizing Readings in Images of Electric Circuit Inspection Meters Based on Deep Learning

A Novel Method for Recognizing Readings in Images of Electric Circuit Inspection Meters Based on Deep Learning

High-Speed Wide-Field Imaging of Microcircuitry Using Nitrogen Vacancies in Diamond

The ability to measure the passage of electrical current with high spatial and temporal resolution is vital for applications ranging from inspection of microscopic electronic circuits to biosensing. The ability to image such signals passively and remotely is of great importance, in order to measure without invasive disruption of the system under study or the signal itself. A recent approach to achieving this utilizes point defects in solid-state materials; in particular, nitrogen-vacancy centers in diamond. Acting as a high-density array of independent sensors, addressable opto-electronically and highly sensitive to factors including temperature and magnetic field, these are ideally suited to microscopic wide-field imaging. In this work, we demonstrate simultaneous spatially and temporally resolved recovery signals from a microscopic lithographically patterned circuit. Through application of a lock-in amplifier camera, we demonstrate micrometer-scale imaging resolution with a millimeter-scale field of view with simultaneous spatially resolved submillisecond (up to 3500 frames ${\mathrm{s}}^{\ensuremath{-}1}$) recovery of dc to kilohertz alternating and broadband pulsed-current electrical signals, without aliasing or undersampling. We demonstrate as examples of our method the recovery of synthetic signals replicating digital pulses in integrated circuits and signals that would be observed in a biological neuronal network in the brain.

Correlative AFM and Scanning Microlens Microscopy for Time-Efficient Multiscale Imaging.

With the rapid evolution of microelectronics and nanofabrication technologies, the feature sizes of large‐scale integrated circuits continue to move toward the nanoscale. There is a strong need to improve the quality and efficiency of integrated circuit inspection, but it remains a great challenge to provide both rapid imaging and circuit node‐level high‐resolution images simultaneously using a conventional microscope. This paper proposes a nondestructive, high‐throughput, multiscale correlation imaging method that combines atomic force microscopy (AFM) with microlens‐based scanning optical microscopy. In this method, a microlens is coupled to the end of the AFM cantilever and the sample‐facing side of the microlens contains a focused ion beam deposited tip which serves as the AFM scanning probe. The introduction of a microlens improves the imaging resolution of the AFM optical system, providing a 3–4× increase in optical imaging magnification while the scanning imaging throughput is improved ≈8×. The proposed method bridges the resolution gap between traditional optical imaging and AFM, achieves cross‐scale rapid imaging with micrometer to nanometer resolution, and improves the efficiency of AFM‐based large‐scale imaging and detection. Simultaneously, nanoscale‐level correlation between the acquired optical image and structure information is enabled by the method, providing a powerful tool for semiconductor device inspection.

FPGA-Based Tensor Compressive Sensing Reconstruction Processor for Terahertz Single-Pixel Imaging Systems

Terahertz (THz) imaging system has great potentials for material identification, security screening, circuit inspection, bioinformatics and bio-imaging because it can penetrate various non-metallic materials and inhibits unique spectral fingerprints of a great variety of optically opaque materials in our daily lives. However, THz emitters and detectors are still extremely expensive. Therefore, the single-pixel compressive sensing imaging technique becomes a potential solution for the implementation of a THz imaging system. This paper presents a tensor-based single-pixel compressive sensing model and a reconstruction algorithm for THz single-pixel imaging systems based on the generalized tensor compressive sensing framework. To accelerate the THz image reconstruction, a low-complexity 2-D compressive sensing processor based on power singular value decomposition method (2DCS-PSVD) was designed and implemented in this paper. In the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$32\times32$ </tex-math></inline-formula> single-pixel THz imaging system, the 2DCS-PSVD algorithm requires 78.9% complexity of the modified generalized tensor compressive sensing parallel algorithm (GTCS-P) with little image quality degradation. The 2DCS-PSVD processor was further designed and implemented in the Xilinx ZCU102 SOC FPGA plate-form. The proposed FPGA-based tensor-based compressive sensing processor achieved a throughput of 1127 frames/sec and had the highest normalized hardware efficiency compared to other state-of-the-art works in the literature.

Application of differential countermeasure machine learning model in the field of UAV circuit inspection

In this paper, we establish one-objective differential game equations for one-to-one attack and defense in a two-dimensional plane. Through calculation and visual analysis, obtain the optimal pursuit path movement trajectory, and through machine learning method to training UAV, using cycle process of simulation, output with time growth each cycle pursuit path results, by comparing the movement trajectory image of the pursuit results and find the sheep just escape critical point exit. After that, the angle difference between the two initial positions was changed and tested again to enable the UAV to learn the optimal escape strategy more comprehensively, thus making a more precise path selection. Finally, this method can be reasonably evaluated.

Spatial Location in Integrated Circuits through Infrared Microscopy.

In this paper, we present an infrared microscopy based approach for structures’ location in integrated circuits, to automate their secure characterization. The use of an infrared sensor is the key device for internal integrated circuit inspection. Two main issues are addressed. The first concerns the scan of integrated circuits using a motorized optical system composed of an infrared uncooled camera combined with an optical microscope. An automated system is required to focus the conductive tracks under the silicon layer. It is solved by an autofocus system analyzing the infrared images through a discrete polynomial image transform which allows an accurate features detection to build a focus metric robust against specific image degradation inherent to the acquisition context. The second issue concerns the location of structures to be characterized on the conductive tracks. Dealing with a large amount of redundancy and noise, a graph-matching method is presented—discriminating graph labels are developed to overcome the redundancy, while a flexible assignment optimizer solves the inexact matching arising from noises on graphs. The resulting automated location system brings reproducibility for secure characterization of integrated systems, besides accuracy and time speed increase.

Design of a Rectangular Pickup Coil Fabricated on a PCB Using WBG Power Semiconductor in Discrete Package

Power semiconductors based on wide bandgap (WBG) devices are capable of fast switching and have low on-resistance. Accordingly, a fast sensor with a higher bandwidth is required for circuit inspection based on switch current measurements. Thus, it is necessary to have a current sensor in the printed circuit board (PCB) circuit for diagnosis and protection of the surface mount device (SMD) type circuit system. Accordingly, a pickup coil with the advantages of a high degree of sensor configuration freedom, wide bandwidth, and low cost can be a good alternative. This study analyzes the influence of coil shape and parameters on sensor design as a guideline for embedding a pickup coil in an SMD-type PCB circuit of a WBG power semiconductor-based, half-bridge structure. The mutual inductance and self-inductance values of the coil are considered large variables in the design of a sensor coil for simultaneously maintaining high bandwidth and sensor sensitivity. Therefore, magnetic and frequency response analyses were conducted to verify the correlation with inductance, the influence of coupling capacitance, and the influence of the magnetic field formation via the current flowing through the external trace inside the PCB. The coil model is verified and discussed through simulation and double pulse tests.

Electronic Circuit Failure Detection Using Thermal Image

This inspection of electronic circuits can be performed either by connection with voltage supply and without voltage supply. However, inspections during the working circuit may invite serious harm and damage to the components in the circuit. Usually, the method used is to measure the current and voltage values in the circuit based on the reading reference when the circuit is in normal condition. There is another method that can help check the current circuit condition by using image processing method. In this paper, we presented our study on electronic component failure detection using thermal image processing. The thermal image was collected from linear regulated dc power supply. The observation is focused on the thermal produce by capacitor and voltage regulator IC. The image has been analysed using Red Green Blue (RGB) and Hue Saturation Value (HSV) colour space. The pixel of colour was analysed using mean value. The result showed there is significant different heat produced by the component in normal condition and failure condition. Through the observation, it was found that the high heat was recorded if wrong polarity of the components in the circuit.

Detection of Conductive Particles in TFT-LCD Circuit Using Generative Adversarial Networks

The inspection of conductive particles is a crucial step in the Thin Film Transistor Liquid Crystal Display (TFT-LCD) circuit detection process since only high-quality deformed particles have the conductive effect in the circuit. The main task of detecting conduction particles is to locate and count the valid particles accurately, which is a high challenge due to various difficulties such as the uneven illumination, different sizes to aggregation and overlap between particles, etc. Traditional detection algorithms need to manually set a large number of artificial thresholds, which limits their adaptability. As a result, effective automatic detection of conductive particles is strongly motived in industry. In this paper, a novel particle detection algorithm based on generative adversarial networks (GAN) is proposed for TFT-LCD circuit inspection system. The backbone architecture of the generator is based on a compact end-to-end neural network with multi-scale convolution blocks for well utilizing the multiscale spatial features. And the discriminator is designed to detect and correct high-order inconsistencies for real-fake images. Moreover, Coarse to Fine training strategy and Loss functions Coordination strategy are further proposed to improve the detection quality. The experiments on the real dataset demonstrate the effectiveness of the proposed methods for the detection of valid conductive particles compared to the state-of-the-art methods.

Algorithm for automated visual inspection of MMIC using a classifier based on neural networks

We present the algorithm for automated visual inspection of microwave monolithic integrated circuits (MMIC) using computer vision and artificial neural networks. The artificial neural network classifies each pixel of a microphotograph to a certain photomask area. The algorithm detects defectiveness of an MMIC according to classification result and photomask comparison.

Software Automation and Optimization of an X-ray Microscope Custom Designed for Integrated Circuit Inspection

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Beyond the Blackbox: Repurposing ROM Hacking for Feminist Hacking/Making Practices

While much interest in feminist technology looks to future inventions, dead or obsolete communication media, such as older smartphones, offers spaces in which to hack into effaced gendered narratives, specifically through physical processes of deconstruction and circuit bending. Thus, this practice brings attention to the tasks and narratives of circuit inspection and soldering of female … Continue reading Beyond the Blackbox: Repurposing ROM Hacking for Feminist Hacking/Making Practices →

Automatic Safety Routing Inspection of the Electric Circuits Based on UAV Light Detection and Ranging

With the higher and higher demands on the electric circuits of our country, the scale of overhead transmission line and its covering area have been expanding. As a result, the traditional regular routing inspection of electric circuits by man can’t meet the needs of people’s demands on the stability of power system. The application and development of UAV LIDAR and scanning technology has provided a new platform for the automatic safety routing inspection of electric circuits. Moreover, the modern safety routing inspection of electric circuits has been deeply studied and widely applied due to the UAV remote sensing technology and LIDAR and electronic scanning technology.

An Embedded Marked Point Process Framework for Three-Level Object Population Analysis.

In this paper, we introduce a probabilistic approach for extracting the complex hierarchical object structures from the digital images used by various vision applications. The proposed framework extends conventional marked point process (MPP) models by: 1) admitting object-subobject ensembles in parent-child relationships; and 2) allowing corresponding objects to form coherent object groups, by a Bayesian segmentation of the population. Different from earlier, highly domain specific attempts on MPP generalization, the proposed model is defined at an abstract level, providing clear interfaces for applications in various domains. We also introduce a global optimization process for the multi-layer framework for finding optimal entity configurations, considering the observed data, prior knowledge, and interactions between the neighboring and the hierarchically related objects. The proposed method is demonstrated in three different application areas: built in area analysis in remotely sensed images, traffic monitoring on airborne, and mobile laser scanning (Lidar) data and optical circuit inspection. A new benchmark database is published for the three test cases, and the model's performance is quantitatively evaluated.

Revisited generalized substitution theorem and its consequences for circuit analysis

SummaryThe Substitution Theorem (ST) is generally perceived as a mere theoretical curiosity. In this paper, a formerly derived generalized ST (GST) is carefully revised, which leads to both a Weak Revisited GST (RGST) and a Strong RGST (characterized by noticeably relaxed hypotheses with respect to the GST). Then, despite the common opinion about the ST, such RGSTs are showed to be powerful analytical tools to generalize, make rigorous and rigorously prove several classic results of Circuit Theory, namely: the Substitution Theorem for Multiterminal Circuits, the Source‐Shift Theorem, the Thévenin–Norton Theorem, the Miller Theorem alongside its Dual, and the Augmentation Principle. More specifically, the Substitution Theorem for Multiterminal Circuits is extended to an arbitrary set of sources, possibly including nullors. The Source‐Shift Theorem is rigorously derived, and possible related ambiguities are removed. Also, all possible hybrid forms of the Thévenin–Norton Theorem for multiports are individuated, and a precise operative procedure for calculating the relevant entities is provided for all cases. Furthermore, the Miller Theorem and its Dual are extended to an arbitrary number of variables and to multiports. As to the Augmentation Principle, the constraint regarding the linearity of the augmenting resistors is removed. Finally, thoroughly worked examples are given in which the aforementioned noteworthy consequences of the RGSTs are proved to be efficient tools for analysis by inspection of linear and nonlinear circuits. Among the other things, systematic pencil‐and‐paper procedures for DC‐point and input‐output (or driving‐point) characteristic calculation in nonlinear networks are derived and applied to circuits with considerably complex topology. Copyright © 2016 John Wiley &amp; Sons, Ltd.

EMI Prediction of Switching Converters

This paper addresses the simulation of the conducted electromagnetic interference produced by circuits with periodically switching elements. The proposed method allows for the computation of their steady-state responses by means of augmented linear time-invariant equivalents built from circuit inspection only, and standard tools for circuit analysis. The approach is demonstrated on a real dc–dc boost converter by comparing simulation results with real measurements.

Millimeter-wave near-field imaging with bow-tie antennas.

A near-field reflectometry experiment operating at 60 GHz is built in view of material and circuit inspection. Experiments are always obtained in constant height mode of operation. The bow-tie near-field probe acts mostly as a linearly-polarized electric dipole and allows strongly subwavelength resolution of ≈ λ/130. Its interaction with sample is shown polarization dependent and sensitive to both the local topography and the local dielectric constant or metal conductivity. Resonant and non-resonant probes are both evaluated.

Steady-State Analysis of Switching Power Converters Via Augmented Time-Invariant Equivalents

This letter addresses the simulation of the steady-state response of switching power converters. The proposed approach is based on the interpretation of the voltage and current variables of a periodically switched linear circuit in terms of a series expansion and on the generation of augmented time-invariant constitutive relations of the circuit elements. The circuit solution is obtained from an augmented time-invariant nodal equation generated from topological information and circuit inspection only. The feasibility and strength of the approach are demonstrated on a dc-dc boost converter.

BENEFITS OF TRANSMISSION LINE METAL-INSULATOR-METAL CAPACITORS IN MASS PRODUCTION OF RF CIRCUITS

Coupling capacitors or DC blocks are essential tuning elements in RF/microwave applications. Their role becomes imperative in cascade amplifiers to isolate drain voltages of preceding MMIC from the gate voltage of the following chip where both RF and DC signals are carried through the same line. The purpose of this study is to explain the benefits of a newly designed thin film coupling capacitor called as transmission line metal-insulator-metal capacitor (TL MIM Cap), which serves as a DC block capacitor in microwave circuits. This novel structure provides a unique solution, which cannot be achieved with traditional single layer ceramic capacitor (SLC) structure. It combines two discrete circuit elements into one: “Microstrip transmission line of required length and width” with a “serially attached coupling capacitor”. Thin film capacitive layers ranged from 0.5pF to 50pF, which are typically needed for microwave frequencies within 1–40 GHz, constructed and embedded into 50 Ohm impedance transmission lines in series. Substrates like quartz, glass, or alumina can be used to minimize losses and to achieve higher RF/microwave performance. We used copper traces as conductive layers for optimal conductivity. After manufacturing TL MIM Caps, we tested several capacitance values for 1pF, 5pF, 15pF and 30pF corresponding to a wide frequency range. The RF tests we performed showed that TL MIM Caps exhibited a minimum of 20dB return loss and a maximum of 0.3 dB insertion loss at 1–40GHz range. We also found our technique comes with some workmanship advantages in high frequency circuit assembly as follows: Traditional coupling capacitor attachment with silver epoxy on top of a microstrip transmission line is a manual operation, which requires well trained and experienced technicians. In contrast, using the TL MIM Caps in our high frequency hybrid modules, we found that the process caused errors were eliminated such as the micro short circuit effect caused by conductive epoxy. Therefore we improved yield in assembly stage of the circuits. In addition, improvements are observed in production processes such as less consumption of adhesives (epoxy), no technician failure caused wastes, elimination of extra curing process to attach capacitors, no short circuit inspection, rework, or re-cure operations to fix assembly errors. Last but not least, blocking capacitors are embedded into the microstrip transmission lines in TL MIM Caps. This ensures that having the lowest possible impedance since very short wire bond exists from the bond pad of the TL MIM Cap to the adjacent circuit element.