Automated X-ray Defect Inspection on Occluded BGA Balls Using Hybrid Algorithm

Automated X-ray defect inspection of occluded objects has been an essential topic in semiconductors,autonomous vehicles,and artificial intelligence devices.However,there are few solutions to segment occluded objects in the X-ray inspection efficiently.In particular,in the Ball Grid Array inspection of X-ray images,it is difficult to accurately segment the regions of occluded solder balls and detect defects inside solder balls.In this paper,we present a novel automatic inspection algorithm that segments solder balls,and detects defects fast and efficiently when solder balls are occluded.The proposed algorithm consists of two stages.In the first stage,the defective candidates or defects are determined through the following four steps:(i)image preprocessing such as noise removal,contrast enhancement,binarization,connected component,and morphology,(ii)limiting the inspec-tion area to the ball regions and determining if the ball regions are occluded,(iii)segmenting each ball region into one or more regions with similar gray values,and(iv)determining whether there are defects or defective candidates in the regions using a weighted sum of local threshold on local variance.If there are defective candidates,the determination of defects is finally made in the following stage.In the second stage,defects are detected using the automated inspection technique based on oblique computed tomography.The 3D precision inspection process is divided into four steps:(i)obtaining 360 projection images(one image per degree)rotating the object from 0 to 360 degrees,(ii)reconstructing a 3D image from the 360 projected images,(iii)finding the center slice of gravity for solder balls from the axial slice images in the z-direction,and getting the inspection intervals between the upper bound and the lower bound from the center slice,and(iv)finally determining whether there are defects in the averaged image of solder balls.The proposed hybrid algorithm is robust for segmenting the defects inside occluded solder balls,and improves the performance of solder ball segmentation and defect detection algorithm.Experimental results show an accuracy of more than 97%.

A Railway Fastener Inspection Method Based on Abnormal Sample Generation

Regular fastener detection is necessary to ensure the safety of railways.However,the number of abnormal fasteners is significantly lower than the number of normal fasteners in real railways.Existing supervised inspectionmethods have insufficient detection ability in cases of imbalanced samples.To solve this problem,we propose an approach based on deep convolutional neural networks(DCNNs),which consists of three stages:fastener localization,abnormal fastener sample generation based on saliency detection,and fastener state inspection.First,a lightweight YOLOv5s is designed to achieve fast and precise localization of fastener regions.Then,the foreground clip region of a fastener image is extracted by the designed fastener saliency detection network(F-SDNet),combined with data augmentation to generate a large number of abnormal fastener samples and balance the number of abnormal and normal samples.Finally,a fastener inspection model called Fastener ResNet-8 is constructed by being trained with the augmented fastener dataset.Results show the effectiveness of our proposed method in solving the problem of sample imbalance in fastener detection.Qualitative and quantitative comparisons show that the proposed F-SDNet outperforms other state-of-the-art methods in clip region extraction,reaching MAE and max F-measure of 0.0215 and 0.9635,respectively.In addition,the FPS of the fastener state inspection model reached 86.2,and the average accuracy reached 98.7%on 614 augmented fastener test sets and 99.9%on 7505 real fastener datasets.

Calibration of CO and CO2 Monitors Used in Periodic Inspection of Vehicles at Fixed Stations for Environmental Control

Global efforts for environmental cleanliness through the control of gaseous emissions from vehicles are gaining momentum and attracting increasing attention. Calibration plays a crucial role in these efforts by ensuring the quantitative assessment of emissions for informed decisions on environmental treatments. This paper describes a method for the calibration of CO/CO2 monitors used for periodic inspections of vehicles in cites. The calibration was performed in the selected ranges: 900 - 12,000 µmol/mol for CO and 2000 - 20,000 µmol/mol for CO2. The traceability of the measurement results to the SI units was ensured by using certified reference materials from CO/N2 and CO2/N2 primary gas mixtures. The method performance was evaluated by assessing its linearity, accuracy, precision, bias, and uncertainty of the calibration results. The calibration data exhibited a strong linear trend with R² values close to 1, indicating an excellent fit between the measured values and the calibration lines. Precision, expressed as relative standard deviation (%RSD), ranged from 0.48 to 4.56% for CO and from 0.97 to 3.53% for CO2, staying well below the 5% threshold for reporting results at a 95% confidence level. Accuracy measured as percent recovery, was consistently high (≥ 99.1%) for CO and ranged from 84.90% to 101.54% across the calibration range for CO2. In addition, the method exhibited minimal bias for both CO and CO2 calibrations and thus provided a reliable and accurate approach for calibrating CO/CO2 monitors used in vehicle inspections. Thus, it ensures the effectiveness of exhaust emission control for better environment.

High-speed railway track components inspection framework based on YOLOv8 with high-performance model deployment

Railway inspection poses significant challenges due to the extensive use of various components in vast railway networks,especially in the case of high-speed railways.These networks demand high maintenance but offer only limited inspection windows.In response,this study focuses on developing a high-performance rail inspection system tailored for high-speed railways and railroads with constrained inspection timeframes.This system leverages the latest artificial intelligence advancements,incorporating YOLOv8 for detection.Our research introduces an efficient model inference pipeline based on a producer-consumer model,effectively utilizing parallel processing and concurrent computing to enhance performance.The deployment of this pipeline,implemented using C++,TensorRT,float16 quantization,and oneTBB,represents a significant departure from traditional sequential processing methods.The results are remarkable,showcasing a substantial increase in processing speed:from 38.93 Frames Per Second(FPS)to 281.06 FPS on a desktop system equipped with an Nvidia RTX A6000 GPU and from 19.50 FPS to 200.26 FPS on the Nvidia Jetson AGX Orin edge computing platform.This proposed framework has the potential to meet the real-time inspection requirements of high-speed railways.

A path planning method for robot patrol inspection in chemical industrial parks

Safety patrol inspection in chemical industrial parks is a complex multi-objective task with multiple degrees of freedom.Traditional pointer instruments with advantages like high reliability and strong adaptability to harsh environment,are widely applied in such parks.However,they rely on manual readings which have problems like heavy patrol workload,high labor cost,high false positives/negatives and poor timeliness.To address the above problems,this study proposes a path planning method for robot patrol in chemical industrial parks,where a path optimization model based on improved iterated local search and random variable neighborhood descent(ILS-RVND)algorithm is established by integrating the actual requirements of patrol tasks in chemical industrial parks.Further,the effectiveness of the model and algorithm is verified by taking real park data as an example.The results show that compared with GA and ILS-RVND,the improved algorithm reduces quantification cost by about 24%and saves patrol time by about 36%.Apart from shortening the patrol time of robots,optimizing their patrol path and reducing their maintenance loss,the proposed algorithm also avoids the untimely patrol of robots and enhances the safety factor of equipment.

From manual to automated fabric inspection

Uster,Switzerland,28th March 2024–Uster Technologies offers a flexible solution to upgrade fabric inspection from manual to automated.Integration in existing production lines is quick and easy,and the data flow also brings extra benefits.It means fabric producers can significantly improve their yield with fast,accurate quality monitoring.

Analysis of the Application of Bridge Rapid Inspection and Evaluation Technology

Rapid bridge inspection and evaluation mainly uses information technology to test the quality of bridge infrastructure and structures,integrates the test results with the existing management system,completes the bridge status assessment,establishes information management files to provide bridge disease problem inspection and analysis,and provides support for the application of disposal measures.This paper briefly discusses the necessity of applying rapid inspection and evaluation technology and analyzes the bridge’s rapid inspection and evaluation content,inspection system,and application process.We look forward to the future application prospects of this technology and supporting those in this field.

Defect Inspection Technology for Steel Truss Suspension Bridges

Steel truss suspension bridges are prone to developing defects after prolonged use.These defects may include corrosion of the main cable or the steel truss.To ensure the normal and safe functioning of the suspension bridge,it is necessary to inspect for defects promptly,understand the cause of the defect,and locate it through the use of inspection technology.By promptly addressing defects,the suspension bridge’s safety can be ensured.The author has analyzed the common defects and causes of steel truss suspension bridges and proposed specific inspection technologies.This research is intended to aid in the timely discovery of steel truss suspension bridge defects.

Surface form inspection with contact coordinate measurement:a review

Parts with high-quality freeform surfaces have been widely used in industries,which require strict quality control during the manufacturing process.Among all the industrial inspection methods,contact measurement with coordinate measuring machines or computer numerical control machine tool is a fundamental technique due to its high accuracy,robustness,and universality.In this paper,the existing research in the contact measurement field is systematically reviewed.First,different configurations of the measuring machines are introduced in detail,which may have influence on the corresponding sampling and inspection path generation criteria.Then,the entire inspection pipeline is divided into two stages,namely the pre-inspection and post-inspection stages.The typical methods of each sub-stage are systematically overviewed and classified,including sampling,accessibility analysis,inspection path generation,probe tip radius compensation,surface reconstruction,and uncertainty analysis.Apart from those classical research,the applications of the emerging deep learning technique in some specific tasks of measurement are introduced.Furthermore,some potential and promising trends are provided for future investigation.

X-ray在鱼体组织及微量元素检测中的应用

鱼类硬质组织物,特别是骨骼支持鱼体和保护其体内器官的组织,对其进行特征检测分析是研究鱼类游泳运动、鱼类解剖、鱼体建模等的数据基础。随着X-ray技术的发展和国产设备的广泛应用,其仪器设备成本明显降低,使得X-ray在渔业研究与自动化生产中的应用成为可能。首先介绍了X-ray技术的基本原理与其在鱼体组织检测中的应用,X-ray技术在鱼体组织及微量元素检测中的应用主要分为鱼类组织器官的无损检测和鱼体微量元素检测两部分,其中分别介绍了包括照相法、数字成像法、衍射技术和吸收光谱法等X-ray技术;然后综述其在鱼体组织器官建模、鱼骨检测、鱼类化石研究、鱼耳石分析和鱼体微量元素检测方面的应用,总结了Xray在渔业领域应用中存在的问题;最后对X-ray的渔业应用方向进行展望。

The Soft X-ray Imager(SXI)on the SMILE Mission

The Soft X-ray Imager(SXI)is part of the scientific payload of the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.SMILE is a joint science mission between the European Space Agency(ESA)and the Chinese Academy of Sciences(CAS)and is due for launch in 2025.SXI is a compact X-ray telescope with a wide field-of-view(FOV)capable of encompassing large portions of Earth’s magnetosphere from the vantage point of the SMILE orbit.SXI is sensitive to the soft X-rays produced by the Solar Wind Charge eXchange(SWCX)process produced when heavy ions of solar wind origin interact with neutral particles in Earth’s exosphere.SWCX provides a mechanism for boundary detection within the magnetosphere,such as the position of Earth’s magnetopause,because the solar wind heavy ions have a very low density in regions of closed magnetic field lines.The sensitivity of the SXI is such that it can potentially track movements of the magnetopause on timescales of a few minutes and the orbit of SMILE will enable such movements to be tracked for segments lasting many hours.SXI is led by the University of Leicester in the United Kingdom(UK)with collaborating organisations on hardware,software and science support within the UK,Europe,China and the United States.

Global hybrid simulations of soft X-ray emissions in the Earth’s magnetosheath

Earth’s magnetopause is a thin boundary separating the shocked solar wind plasma from the magnetospheric plasmas,and it is also the boundary of the solar wind energy transport to the magnetosphere.Soft X-ray imaging allows investigation of the large-scale magnetopause by providing a two-dimensional(2-D)global view from a satellite.By performing 3-D global hybrid-particle-in-cell(hybrid-PIC)simulations,we obtain soft X-ray images of Earth’s magnetopause under different solar wind conditions,such as different plasma densities and directions of the southward interplanetary magnetic field.In all cases,magnetic reconnection occurs at low latitude magnetopause.The soft X-ray images observed by a hypothetical satellite are shown,with all of the following identified:the boundary of the magnetopause,the cusps,and the magnetosheath.Local X-ray emissivity in the magnetosheath is characterized by large amplitude fluctuations(up to 160%);however,the maximum line-of-sight-integrated X-ray intensity matches the tangent directions of the magnetopause well,indicating that these fluctuations have limited impact on identifying the magnetopause boundary in the X-ray images.Moreover,the magnetopause boundary can be identified using multiple viewing geometries.We also find that solar wind conditions have little effect on the magnetopause identification.The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will provide X-ray images of the magnetopause for the first time,and our global hybrid-PIC simulation results can help better understand the 2-D X-ray images of the magnetopause from a 3-D perspective,with particle kinetic effects considered.

Low-Cost Real-Time Automated Optical Inspection Using Deep Learning and Attention Map

The recent trends in Industry 4.0 and Internet of Things have encour-aged many factory managers to improve inspection processes to achieve automa-tion and high detection rates.However,the corresponding cost results of sample tests are still used for quality control.A low-cost automated optical inspection system that can be integrated with production lines to fully inspect products with-out adjustments is introduced herein.The corresponding mechanism design enables each product to maintain afixed position and orientation during inspec-tion to accelerate the inspection process.The proposed system combines image recognition and deep learning to measure the dimensions of the thread and iden-tify its defects within 20 s,which is lower than the production-line productivity per 30 s.In addition,the system is designed to be used for monitoring production lines and equipment status.The dimensional tolerance of the proposed system reaches 0.012 mm,and a 100%accuracy is achieved in terms of the defect reso-lution.In addition,an attention-based visualization approach is utilized to verify the rationale for the use of the convolutional neural network model and identify the location of thread defects.

Finding the magnetopause location using soft X-ray observations and a statistical inverse method

Variability in the location and shape of the dayside magnetopause is attributed to magnetic reconnection,a fundamental process that enables the transfer of mass,energy,and momentum from the solar wind into the magnetosphere.The spatial and temporal properties of the magnetopause,under varying solar and magnetospheric conditions,remain largely unknown because empirical studies using in-situ observations are challenging to interpret.Global wide field-of-view(FOV)imaging is the only means to simultaneously observe the spatial distribution of the plasma properties over the vast dayside magnetospheric region and,subsequently,quantify the energy transport from the interplanetary medium into the terrestrial magnetosphere.Two upcoming missions,ESA/CAS SMILE and NASA’s LEXI will provide wide-field imagery of the dayside magnetosheath in soft X-rays,an emission generated by charge exchange interactions between high charge-state heavy ions of solar wind origin and exospheric neutral atoms.High-cadence two-dimensional observations of the magnetosheath will allow the estimation of dynamic properties of its inner boundary,the magnetopause,and enable studies of its response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation.This work introduces a statistically-based estimation approach based on inverse theory to estimate the spatial distribution of magnetosheath soft X-ray emissivities and,with this,identify the location of the magnetopause over the Sun−Earth line.To do so,we simulate the magnetosheath structure using the MHD-based OpenGGCM model and generate synthetic soft X-ray images using LEXI’s orbit and attitude information.Our results show that 3-D estimations using the described statistically-based technique are robust against Poisson-distributed shot noise inherent to soft X-ray images.Also,our proposed methodology shows that the accuracy of both three-dimensional(3-D)estimation and the magnetopause standoff distance calculation highly depends on the observational point.

Two methods for separating the magnetospheric solar wind charge exchange soft X-ray emission from the diffuse X-ray background

Solar wind charge exchange(SWCX)is the process of solar wind high-valence ions exchanging charges with neutral components and generating soft X-rays.Recently,detecting the SWCX emission from the magnetosphere is proposed as a new technique to study the magnetosphere using panoramic soft X-ray imaging.To better prepare for the data analysis of upcoming magnetospheric soft X-ray imaging missions,this paper compares the magnetospheric SWCX emission obtained by two methods in an XMM-Newton observation,during which the solar wind changed dramatically.The two methods differ in the data used to fit the diffuse X-ray background(DXB)parameters in spectral analysis.The method adding data from the ROSAT All-Sky Survey(RASS)is called the RASS method.The method using the quiet observation data is called the Quiet method,where quiet observations usually refer to observations made by the same satellite with the same target but under weaker solar wind conditions.Results show that the spectral compositions of magnetospheric SWCX emission obtained by the two methods are very similar,and the changes in intensity over time are highly consistent,although the intensity obtained by the RASS method is about 2.68±0.56 keV cm^(-2)s^(-1)sr^(-1)higher than that obtained by the Quiet method.Since the DXB intensity obtained by the RASS method is about 2.84±0.74 keV cm^(-2)s^(-1)sr^(-1)lower than that obtained by the Quiet method,and the linear correlation coefficient between the difference of SWCX and DXB obtained by the two methods in diffe rent energy band is close to-1,the diffe rences in magnetospheric SWCX can be fully attributed to the diffe rences in the fitted DXB.The difference between the two methods is most significant when the energy is less than 0.7 keV,which is also the main energy band of SWCX emission.In addition,the difference between the two methods is not related to the SWCX intensity and,to some extent,to solar wind conditions,because SWCX intensity typically va ries with the solar wind.In summary,both methods are robust and reliable,and should be considered based on the best available options.

SMILE soft X-ray Imager flight model CCD370 pre-flight device characterisation

Throughout the SMILE mission the satellite will be bombarded by radiation which gradually damages the focal plane devices and degrades their performance.In order to understand the changes of the CCD370s within the soft X-ray Imager,an initial characterisation of the devices has been carried out to give a baseline performance level.Three CCDs have been characterised,the two flight devices and the flight spa re.This has been carried out at the Open University in a bespo ke cleanroom measure ment facility.The results show that there is a cluster of bright pixels in the flight spa re which increases in size with tempe rature.However at the nominal ope rating tempe rature(-120℃) it is within the procure ment specifications.Overall,the devices meet the specifications when ope rating at -120℃ in 6 × 6 binned frame transfer science mode.The se rial charge transfer inefficiency degrades with temperature in full frame mode.However any charge losses are recovered when binning/frame transfer is implemented.

Estimating the subsolar magnetopause position from soft X-ray images using a low-pass image filter

The Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)missions will image the Earth’s dayside magneto pause and cusps in soft X-rays after their respective launches in the near future,to specify glo bal magnetic reconnection modes for varying solar wind conditions.To suppo rt the success of these scientific missions,it is critical to develop techniques that extract the magnetopause locations from the observed soft X-ray images.In this research,we introduce a new geometric equation that calculates the subsolar magnetopause position(RS)from a satellite position,the look direction of the instrument,and the angle at which the X-ray emission is maximized.Two assumptions are used in this method:(1)The look direction where soft X-ray emissions are maximized lies tangent to the magnetopause,and(2)the magnetopause surface near the subsolar point is almost spherical and thus RSis nea rly equal to the radius of the magneto pause curvature.We create synthetic soft X-ray images by using the Open Geospace General Circulation Model(OpenGGCM)global magnetohydrodynamic model,the galactic background,the instrument point spread function,and Poisson noise.We then apply the fast Fourier transform and Gaussian low-pass filte rs to the synthetic images to re move noise and obtain accurate look angles for the soft X-ray pea ks.From the filte red images,we calculate RS and its accuracy for different LEXI locations,look directions,and solar wind densities by using the OpenGGCM subsolar magnetopause location as ground truth.Our method estimates RS with an accuracy of<0.3 RE when the solar wind density exceeds>10 cm-3.The accuracy improves for greater solar wind densities and during southward interplanetary magnetic fields.The method ca ptures the magnetopause motion during southwa rd interplaneta ry magnetic field turnings.Consequently,the technique will enable quantitative analysis of the magnetopause motion and help reveal the dayside reconnection modes for dynamic solar wind conditions.This technique will suppo rt the LEXI and SMILE missions in achieving their scientific o bjectives.

Solar wind ion charge state distributions and compound cross sections for solar wind charge exchange X-ray emission

Solar Wind Charge eXchange X-ray(SWCX) emission in the heliosphere and Ea rth’s exosphere is a hard to avoid signal in soft Xray obse rvations of astrophysical targets.On the other hand,the X-ray imaging possibilities offered by the SWCX process has led to an increasing number of future dedicated space missions for investigating the solar wind-terrestrial inte ractions and magnetospheric interfaces.In both cases,accurate modelling of the SWCX emission is key to correctly interpret its signal,and remove it from obse rvations,when needed.In this paper,we compile solar wind abundance measurements from ACE for different solar wind types,and atomic data from literature,including charge exchange cross-sections and emission probabilities,used fo r calculating the compound cross-section a for the SWCX X-ray emission.We calculate a values for charge-exchange with H and He,relevant to soft X-ray energy bands(0.1-2.0 keV)for various solar wind types and solar cycle conditions.

Defect inspection of indoor components in buildings using deep learning object detection and augmented reality

Visual inspection is commonly adopted for building operation,maintenance,and safety.The durability and defects of components or materials in buildings can be quickly assessed through visual inspection.However,implementations of visual inspection are substantially time-consuming,labor-intensive,and error-prone because useful auxiliary tools that can instantly highlight defects or damage locations from images are not available.Therefore,an advanced building inspection framework is developed and implemented with augmented reality(AR)and real-time damage detection in this study.In this framework,engineers should walk around and film every corner of the building interior to generate the three-dimensional(3D)environment through ARKit.Meanwhile,a trained YOLOv5 model real-time detects defects during this process,even in a large-scale field,and the defect locations indicating the detected defects are then marked in this 3D environment.The defects areas can be measured with centimeter-level accuracy with the light detection and ranging(LiDAR)on devices.All required damage information,including defect positions and sizes,is collected at a time and can be rendered in the 2D and 3D views.Finally,this visual inspection can be efficiently conducted,and the previously generated environment can also be loaded to re-localize existing defect marks for future maintenance and change observation.Moreover,the proposed framework is also implemented and verified by an underground parking lot in a building to detect and quantify surface defects on concrete components.As seen in the results,the conventional building inspection is significantly improved with the aid of the proposed framework in terms of damage localization,damage quantification,and inspection efficiency.

Comparison of three fundus inspection methods during phacoemulsification in diabetic white cataract

AIM:To investigate whether Wild Field Imaging System(WFIS SW-8000),25G endoilluminator,and intraoperative optical coherence tomography(iOCT)can perform realtime screening and diagnosing in patients with suspicious diabetic retinopathy(DR)during phacoemulsification,especially in cases of white cataract.METHODS:A cross-sectional study was carried out.A total of 204 dense diabetic cataractous eyes of 204 patients with suspected DR treated from April 2020 to March 2021 were included.Phacoemulsification combined with intraocular lens implantation was performed.Following the removal of the lens opacity,the 25G endoilluminator,fundus photography,and iOCT were performed successively.Optical coherence tomography(OCT)and/or fundus fluorescein angiography(FFA)were used to verify the fundus findings postoperatively.Intraoperative and postoperative results were compared to verify the accuracy of intraoperative diagnosis in each group.RESULTS:Intraoperative and postoperative examinations revealed 58 and 62 eyes with DR,respectively(positive rate,28.43%and 30.39%,respectively).During the phacoemulsification,WFIS SW-8000 detected 44 eyes with DR(the detection rate,70.97%);25G endo-illuminator found 56 eyes with DR(the detection rate,90.32%);iOCT found 46 eyes with DR(the detection rate,74.19%);and 58 eyes with DR were found by combining the three methods(the detection rate,93.55%).There were statistically significant differences in the diagnostic sensitivity for DR among the methods(χ^(2)=16.36,P=0.001).CONCLUSION:WFIS SW-8000,25G endo-illuminator,iOCT,and especially their combination can be used to inspect the fundus and detect DR intraoperatively;they are helpful for the timely diagnosis and treatment of DR in patients with dense cataract.